APOLLO  is a fully integrated Bayesian fitting pipeline. Its core is written in Python, with extensive use of highly optimized scientific libraries [1]}, [2]}, [3]}, [4]}. It also makes direct use of Diamonds, for which we created both a Python interface as well as direct parsing of the binary output. The pipeline also generates the necessary run files for Diamonds  and analyzes its outputs. It possesses full multi-processing capabilities, allowing for the analysis of multiple stars in parallel when modern multi-core processors are in use. This allows for quick evaluations of large data sets: Our sample of red giants, consisting of 1071 objects with the majority having four years of observation and consisting of around 68 000 data points, takes six hours to complete using the AMD Threadripper architecture with all 32 threads in use. Extrapolating from this, the average run time for one object, including the fit for both models, takes around 20 s. In comparison, performing the analysis sequentially (one star at a time on one thread) takes between five and ten minutes per star.
